3.7T1 Training Materials: Video "Scenario definition" (original) (raw)

Video: "Scenario definition"

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Welcome to this video on “Scenario Definition” in the FABLE Calculator. Our objective is to help you learn, once you have selected your preferred scenarios, to then define them in more detail by changing specific values of the scenarios and implementation rates.

In the last video, we reviewed how changing scenario preferences in the worksheet “Scenario Selection” would lead to different results in the yellow worksheets. In other words: the most basic action of the user of the FABLE Calculator is a scenario selection. The next level of action is to adapt the chosen scenario, by changing several values in the “Scenario Definition” Worksheet. We will look into it with more detail using the example of the scenarios on Afforestation target.

The scenarios on Afforestation target are found in Table S.10, which has two options, in the default version of the Open Source calculator: NoAffor and Bonn Challenge. No Affor means that there is no additional afforestation planned in the country, whereas Bonn Challenge is supposed to convey the pledge that your country has made to this international initiative. If you visit the official website of the Bonn Challenge, you will see that different countries have pledged different quantities of restoring degraded and deforested landscapes. Some countries may have pledged one million hectares, while others pledged much less (100,000 hectares), or much more (eight million hectares). Also, the plan of implementation for these pledges differs in time. Some restoration is expected by 2020, while most of the target is expected to be met by 2030. How could you implement these specifications in the FABLE Calculator?

In the Exercise of the previous video, we compared the two results one can get in the default values of the FABLE Calculator, shown in the current slide. The default specifications of this Afforestation target scenario are: a) an implementation rate or “Timing of the afforestation /reforestation target” specified as “AfforTiming” and a Bonn Challenge of thirty million hectares. Let us see where to find these values, so you learn how to change them as your country requires.

First, we revise the first part of this change: the Implementation Rate Parameter, and the Implementation Coefficient. The implementation rate parameter is used to translate targeted values for 2050, as targeted values for each time step between 2015 and 2050. The implementation coefficient is the share of the difference between the current situation and the 2050 target that is assumed to be achieved in each time-step.

In the Scenarios Definition worksheet, you find these two specifications in the first columns of the worksheet. Namely, the first table of the worksheet entitled “ImplCoefOptions” includes the definition of various types of implementation rates, called in self-describing ways: Linear, Delayed, Fast, etc. These implementation rates are defined by the user, in order to convey how a variable may change in time. As you can see when you look at this table in detail, the difference between each of these types is: based on the desired 2050 target, how much of that share will be implemented in every five-year step of the calculator. For Linear, the 2030 percentage desired is 50% whereas for Delayed it is 35%. You will notice at the end of this table, that there is a specific Implementation rate for Afforestation, called “AfforTiming”, which describes the first major change in 2020 of 60%, which is then progressively increasing by 10% for every five-year time step, until reaching 100% in 2040.

In this way, every scenario that you have selected in the “Scenario Selection” worksheet will be further defined in this “Scenario Definition” worksheet, using a user-preferred implementation rate, among other changes. Now, let us see how the Afforestation scenario is defined here in this worksheet. For this, a useful characteristic of the FABLE Calculator is that, for every table found in the Scenario Selection worksheet (for example, S.10 for Afforestation), there will be at least one table in the Scenario Definition worksheet with the same number. Look now for this S.10 table (s) in this worksheet. See you there!

For this video, we will focus on the first columns of Table S.10a. The first column, entitled “Afforestation/Reforestation scenario” includes all the different scenarios that we have included in the homologous table of the Scenario Selection worksheet, namely Bonn Challenge and NoAffor. For each of these scenarios, the next column defines:

  1. First, the different time steps that have NOT been defined for the preferred Implementation rate in the beginning of the worksheet: 2000, 2005 and 2015, which have a 0% in the table ImplCoefOptions,
  2. Second, the target to be achieved by 2050, which in the default calculator is 30,000 kilohectares for the Bonn Challenge scenario. In summary, this number should match the Bonn Challenge pledge for your country.

What effects do you expect to see when you change some of these parameters, in the LAND worksheet, for the different Afforestation scenarios, which are defined in the FABLE Calculator as belonging to the “New Forest” Category?

----------------------------------- Content ------------------------------------

0:00 - Welcome

0:27 - Scenario Selection vs Scenario Definition

0:58 - Afforestation scenarios as an example

1:36 – What is the Bonn Challenge?

2:19 - How to implement Bonn Challenge in the FABLE Calculator?

2:35 – Implementation rate parameter vs Implementation coefficient

4:49 – How is the Afforestation scenario defined?

6:18 – Putting it all together

6:40 – Links to FABLE Websites (to click on them, also included in the video description)


For more information on the FABLE Calculator:

(https://www.abstract-landscapes.com/fable-calculator)

(https://github.com/FABLE-Github/Fable-Calculator-Documentation-2020/wiki)

For more information on the FABLE Consortium:

(https://www.foodandlandusecoalition.org/fable/)

The 2020 FABLE Report:

(http://pure.iiasa.ac.at/id/eprint/16896/)


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